A semi-supervised methodology for fishing activity detection using the
geometry behind the trajectory of multiple vessels

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A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels

12 July 2022

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Papers citing "A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels"

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Title
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation D. Powers 175 5,293 0 11 Oct 2020
Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning Lucas May Petry Amílcar Soares Júnior V. Bogorny Bruno Brandoli Stan Matwin 63 27 0 07 Apr 2020
Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation Mohammad Etemad Zahra Etemad Amílcar Soares Júnior V. Bogorny Stan Matwin Luís Torgo 13 17 0 23 Mar 2020
GeoTrackNet-A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection Duong Nguyen Rodolphe Vadaine G. Hajduch R. Garello Ronan Fablet 55 90 0 02 Dec 2019
A Multi-task Deep Learning Architecture for Maritime Surveillance using AIS Data Streams Duong Nguyen Rodolphe Vadaine G. Hajduch R. Garello Ronan Fablet 54 104 0 06 Jun 2018
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 601 12,741 0 11 Dec 2014